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Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Honors Statistics Aug 23-8:26 PM Daily Agenda 3. Review Homework C5#7 Aug 23-8:31 PM 1 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Apr 17-8:20 PM Nov 9-5:30 PM 2 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Nov 9-5:34 PM How do you want it - the crystal mumbo-jumbo or statistical probability? Apr 25-10:55 AM 3 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Get rich A survey of 4826 randomly selected young adults (aged 19 to 25) asked, “What do you think are the chances you will have much more than a middle-class income at age 30?” The two-way table shows the responses. Choose a survey respondent at random. Given that the person selected is male, what’s the probability that he answered “almost certain”? P(AC I M) = --------- = 0.2428 If the person selected said “some chance but probably not,” what’s the probability that the person is female? P(F I ScPn) = --------- = 0.5983 Nov 18-8:16 PM 319 261 627 442 765 1207 A Titanic disaster In 1912 the luxury liner Titanic, on its first voyage across the Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. The two-way table gives information about adult passengers who lived and who died, by class of travel. Suppose we choose an adult passenger at random. > (a) Given that the person selected was in first class, what’s the probability that he or she survived? 197 P(Survived I FC) = --------- = 0.6176 319 > (b) If the person selected survived, what’s the probability that he or she was a third-class passenger? 151 P( third class I Survived) = --------- = 0.3416 442 Nov 18-8:17 PM 4 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 60 40 83 17 100 Sampling senators The two-way table describes the members of the U.S. Senate in a recent year. Suppose we select a senator at random. Consider events D: is a democrat, and F: is female. (a) Find P(D | F). Explain what this value means. 13 P(D I F) = --------- = 0.765 17 What is the probability that you are a democrat given that you are a female senator? 76.5% (b) Find P(F | D). Explain what this value means. 13 P(F I D) = --------- = 0.217 What is the probability that you are a female given that you are a democratic senator? 21.7% 60 ARE THESE EVENT INDEPENDENT? ARE GENDER AND PARTY Independent events for the U.S. Senators? Nov 18-8:19 PM Who eats breakfast? The following two-way table describes the 595 students who responded to a school survey about eating breakfast. Suppose we select a student at random. Consider events B: eats breakfast regularly, and M: is male. (a) Find P(B | M). Explain what this value means. 190 P(B I M) = --------- = 0.5938 320 What is the probability that you eat breakfast regularly given that you are a male? 59.38% (b) Find P(M | B). Explain what this value means. 190 P(M I B) = --------- = 0.6333 300 What is the probability that you are a male given that you eat breakfast regularly 63.33% ARE THESE EVENT INDEPENDENT? ARE GENDER AND Breakfast habits Independent events? Nov 18-8:19 PM 5 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Foreign-language study Choose a student in grades 9 to 12 at random and ask if he or she is studying a language other than English. Here is the distribution of results: > (a) What’s the probability that the student is studying a language other than English? P(other than English) = 1 - P(none) = 1 - 0.59 = 0.41 > (b) What is the conditional probability that a student is studying Spanish given that he or she is studying some language other than English? 0.26 P( S I other than English) = -------- = 0.6341 0.41 Nov 18-8:20 PM Income tax returns Here is the distribution of the adjusted gross income (in thousands of dollars) reported on individual federal income tax returns in a recent year: > (a) What is the probability that a randomly chosen return shows an adjusted gross income of $50,000 or more? P(income ≥ 50000) = 0.215 + 0.100 + 0.006 = 0.321 > (b) Given that a return shows an income of at least $50,000, what is the conditional probability that the income is at least $100,000? 0.106 P( income ≥ 100,000 I income ≥ 50,000) = ----------- = 0.3302 0.321 Nov 18-8:21 PM 6 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Teachers and college degrees Select an adult at random. Define events A: person has earned a college degree, and T: person’s career is teaching. Rank the following probabilities from smallest to largest. Justify your answer. P(A) P(T) P(A | T) P(T | A) P(T)... some of the population of adults are teachers P(T I A) ... some people who have college degrees are teachers P(A) ... many people have college degrees P(A I T) ... all teachers have college degrees Nov 18-8:29 PM Tall people and basketball players Select an adult at random. Define events T: person is over 6 feet tall, and B: person is a professional basketball player. Rank the following probabilities from smallest to largest. Justify your answer. P(T) P(B) P(T | B) P(B | T) P(B) ... some people play basketball (few pro) P(B I T) ... some tall people play basketball P(T)... more of the population of adults are tall P(T I B) ... almost all pro basketball players are tall Nov 18-8:22 PM 7 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Facebook versus YouTube A recent survey suggests that 85% of college students have posted a profile on Facebook, 73% use YouTube regularly, and 66% do both. Suppose we select a college student at random and learn that the student has a profile on Facebook. Find the probability that the student uses YouTube regularly. Show your work. FACE NF UTube 0.66 0.07 0.73 0.19 0.08 0.27 0.85 0.15 NU 1.00 0.66 = 0.7765 P( UTube I Face) = ---------0.85 Nov 18-8:22 PM Mac or PC? A recent census at a major university revealed that 40% of its students mainly used Macintosh computers (Macs). The rest mainly used PCs. At the time of the census, 67% of the school’s students were undergraduates. The rest were graduate students. In the census, 23% of the respondents were graduate students who said that they used PCs as their primary computers. Suppose we select a student at random from among those who were part of the census and learn that the student mainly uses a PC. Find the probability that this person is a graduate student. Show your work. MAC PC 0.30 0.37 0.67 Grad 0.10 0.23 0.33 0.40 0.60 1.00 Und 0.23 = 0.383 P(G I PC) = ---------0.60 Nov 18-8:23 PM 8 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Free downloads? Illegal music downloading has become a big problem: 29% of Internet users download music files, and 67% of downloaders say they don’t care if the music is copyrighted.17 What percent of Internet users download music and don’t care if it’s copyrighted? Write the information given in terms of probabilities, and use the general multiplication rule. P( IDC and download) P( IDC I download) = ----------------P(download) x 0.67 = ---------0.29 x = (0.67)(0.29) x = 0.1943 P( IDC and download) = 0.1943 or 19.4% Nov 18-8:23 PM Please place the following in your pocket folder: Aug 20-8:59 PM 9 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Nov 15-10:41 PM Nov 15-10:41 PM 10 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 May 3-6:11 PM May 3-6:12 PM 11 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Nov 16-6:12 PM Nov 16-6:11 PM 12 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Nov 16-6:12 PM Nov 16-6:14 PM 13 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Nov 28-9:45 PM Dec 15-7:03 PM 14 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 HIV testing Enzyme immunoassay (EIA) tests are used to screen blood specimens for the presence of antibodies to HIV, the virus that causes AIDS. Antibodies indicate the presence of the virus. The test is quite accurate but is not always correct. Here are approximate probabilities of positive and negative EIA outcomes when the blood tested does and does not actually contain antibodies to HIV:21 Suppose that 1% of a large population carries antibodies to HIV in their blood. We choose a person from this population at random. Given that the EIA test is positive, find the probability that the person has the antibody. Show your work. Nov 19-3:26 PM Nov 16-6:13 PM 15 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 The probability of a flush A poker player holds a flush when all 5 cards in the hand belong to the same suit. We will find the probability of a flush when 5 cards are dealt. Remember that a deck contains 52 cards, 13 of each suit, and that when the deck is well shuffled, each card dealt is equally likely to be any of those that remain in the deck. (a) We will concentrate on spades. What is the probability that the first card dealt is a spade? What is the conditional probability that the second card is a spade given that the first is a spade? P(spade) = 13/52 = .25 P(spade l spade) = (12/51) = .23529 (b) Continue to count the remaining cards to find the conditional probabilities of a spade on the third, the fourth, and the fifth card given in each case that all previous cards are spades. P(spade l spade l spade) = (11/50) = .22 P(spade l spade l spade l spade) = (10/49) =.2041 P(spade l spade l spade l spade l spade) = (9/48) = .1875 (c) The probability of being dealt 5 spades is the product of the five probabilities you have found. Why? What is this probability? using the extended multiplication rule gives the probability of a flush P(spade flush) = (.25)(.2353)(.22)(.2041)(.1875) = 0.0004952 (d) The probability of being dealt 5 hearts or 5 diamonds or 5 clubs is the same as the probability of being dealt 5 spades. What is the probability of being dealt a flush? multiply answer c by 4 (4)(.0004952) = 0.001981 Nov 20-4:52 PM Rolling dice Suppose you roll two fair, six-sided dice—one red and one green. Are the events “sum is 7” and “green die shows a 4” independent? Justify your answer. Nov 19-3:36 PM 16 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Rolling dice Suppose you roll two fair, six-sided dice—one red and one green. Are the events “sum is 8” and “green die shows a 4” independent? Justify your answer. Nov 19-3:37 PM A skips 75, 78, 91 How do you want it - the crystal mumbo-jumbo or statistical probability? t = tree diagram DO IT!! Apr 25-10:55 AM 17 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Box of chocolates never know what you’re gonna get.” Suppose a candy maker offers a special “Gump box” with 20 chocolate candies that look the same. In fact, 14 of the candies have soft centers and 6 have hard centers. Choose 2 of the candies from a Gump box at random. Draw a tree diagram that shows the sample space of this chance process. P(soft ∩ soft)= P(soft ∩ hard)= P(hard ∩ soft)= P(hard ∩ hard)= Find the probability that one of the chocolates has a soft center and the other one Nov 20-4:03 PM Inspecting switches Draw a tree diagram that shows the sample space of this chance process. P(good ∩ good)= P(good ∩ bad)= 10,000 switches P(bad ∩ good)= P(bad ∩ bad)= Find the probability that both switches are defective. P(bad ∩ bad)= = 0.00999 Nov 20-4:19 PM 18 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 In a recent month, 88% of automobile drivers filled their vehicles with regular gasoline, 2% purchased midgrade gas, and 10% bought premium gas. who bought regular gas, 28% paid with a credit card; of customers who bought midgrade and premium gas, 34% and 42%, respectively, paid with a credit card. Suppose we select a customer at random. Draw a tree diagram to represent this situation. P(reg ∩ credit)= (0.88)(0.28) = 0.2464 P(reg ∩ no credit)=(0.88)(0.72) = 0.6336 regular P(mid ∩ credit)= (0.02)(0.34) =0.0068 midgrade .02 P(mid ∩ no credit)=(0.02)(0.66) = 0.0132 P(prem ∩ credit)= (0.10)(0.42) = 0.042 P(prem ∩ no credit)=(0.10)(0.58) = 0.058 Find the probability that the customer paid with a credit card. Show your work. P(credit) = 0.2464 + 0.0068 + 0.042 = 0.2952 Given that the customer paid with a credit card, find the probability that she bought premium gas. Show your work. P(premium I credit) = ------- = 0.142 Nov 20-4:27 PM Urban voters The voters in a large city are 40% white, 40% black, and 20% Hispanic. (Hispanics may be of any race in official statistics, but here we are speaking of political blocks.) A mayoral candidate anticipates attracting 30% of the white vote, 90% of the black vote, and 50% of the Hispanic vote. Suppose we select a voter at random. Draw a tree diagram to represent this situation. vote +) = 0.28 vote +) = vote +) = 0. 20 0.10 Find the probability that this voter votes for the mayoral candidate. Show your work. Given that the chosen voter plans to vote for the candidate, find the probability that the voter is black. Show your work. Nov 20-4:44 PM 19 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Fundraising by telephone Tree diagrams can organize problems having more than two stages. The figure at top right shows probabilities for a charity calling potential donors by telephone.20 Each person called is either a recent donor, a past donor, or a new prospect. At the next stage, the person called either does or does not pledge to contribute, with conditional probabilities that depend on the donor class to which the person belongs. Finally, those who make a pledge either do or don’t actually make a contribution. Suppose we randomly select a person who is called by the charity. a) What is the probability that the person contributed to the charity? Show your work. P(charity contribution) = (0.5)(0.4)(0.8)+(0.3)(0.3)(0.6)+(0.2)(0.1)(0.5) = 0.224 (b) Given that the person contributed, find the probability that he or she is a recent donor. Show your work. P(recent I contribution) = (0.5)(0.4)(0.8) = 0.7143 0.224 Nov 20-4:51 PM Bright lights? A string of Christmas lights contains 20 lights. The lights are wired in series, so that if any light fails, the whole string will go dark. Each light has probability 0.02 of failing during a 3-year period. The lights fail independently of each other. Find the probability that the string of lights will remain bright for 3 years. Nov 20-4:51 PM 20 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Universal blood donors People with type O-negative blood are universal donors. That is, any patient can receive a transfusion of O-negative blood. Only 7.2% of the American population have O-negative blood. If we choose 10 Americans at random who gave blood, what is the probability that at least 1 of them is a universal donor? P(universal donor) = 0.072 P(universal donorC) = 1-0.072 = 0.928 P(10 in a row are not universal) = (0.928)10 P(at least one) = 1 - P(none are universal donor) P(at least one) = 1 - (0.928)10 = 0.5263 Nov 20-4:51 PM Lost Internet sites Internet sites often vanish or move, so that references to them can’t be followed. In fact, 13% of Internet sites referenced in major scientific journals are lost within two years after publication.22 If we randomly select seven Internet references, from scientific journals, what is the probability that at least one of them doesn’t work two years later? P(lost internet site) = 0.13 P(lost siteC) = 1-0.13 = 0.87 P(7 in a row are not lost site) = (0.87)7 P(at least one) = 1 - P(none are lost) P(at least one) = 1 - (0.87)7 = 0.6227 Nov 20-4:51 PM 21 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Late flights An airline reports that 85% of its flights arrive on time. To find the probability that its next four flights into LaGuardia Airport all arrive on time, can we multiply (0.85)(0.85)(0.85)(0.85)? Why or why not? We cannot multiply to find the answer to this question because the arrival of the next four flights will NOT be INDEPENDENT If one flight is next we should expect that more late flights will follow ... Nov 20-4:52 PM The probability of a flush A poker player holds a flush when all 5 cards in the hand belong to the same suit. We will find the probability of a flush when 5 cards are dealt. Remember that a deck contains 52 cards, 13 of each suit, and that when the deck is well shuffled, each card dealt is equally likely to be any of those that remain in the deck. (a) We will concentrate on spades. What is the probability that the first card dealt is a spade? What is the conditional probability that the second card is a spade given that the first is a spade? P(spade) = 13/52 = .25 P(spade l spade) = (12/51) = .23529 (b) Continue to count the remaining cards to find the conditional probabilities of a spade on the third, the fourth, and the fifth card given in each case that all previous cards are spades. P(spade l spade l spade) = (11/50) = .22 P(spade l spade l spade l spade) = (10/49) =.2041 P(spade l spade l spade l spade l spade) = (9/48) = .1875 (c) The probability of being dealt 5 spades is the product of the five probabilities you have found. Why? What is this probability? using the extended multiplication rule gives the probability of a flush P(spade flush) = (.25)(.2353)(.22)(.2041)(.1875) = 0.0004952 (d) The probability of being dealt 5 hearts or 5 diamonds or 5 clubs is the same as the probability of being dealt 5 spades. What is the probability of being dealt a flush? multiply answer c by 4 (4)(.0004952) = 0.001981 Nov 20-4:52 PM 22 Chapter 5 Section 3 day 3b 2016s Notes.notebook April 19, 2016 Nov 15-7:17 PM 23